Chris Sampson’s journal round-up for 17th December 2018

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

Health related quality of life aspects not captured by EQ-5D-5L: results from an international survey of patients. Health Policy Published 14th December 2018

Generic preference-based measures, such as the EQ-5D, cannot capture all aspects of health-related quality of life. They’re not meant to. Rather, their purpose is to capture just enough information to be able to adequately distinguish between health states with respect to the domains deemed normatively relavent to decisionmakers. The stated aim of this paper is to determine whether people with a variety of chronic conditions believe that their experiences can be adequately represented by the EQ-5D-5L.

The authors conducted an online survey, identifying participants through 320 patient associations across 47 countries. Participants were asked to complete the EQ-5D-5L and then asked if any aspects of their illness, which had a “big impact” on their health, were not captured by the EQ-5D-5L. 1,031 people started the survey and 767 completed it. More than half were from the UK. 51% of respondents said that there was some aspect of health not captured by the EQ-5D-5L. Of them, 19% mentioned fatigue, 12% mentioned medication side effects, 9.5% mentioned co-morbid conditions, and then a bunch of others in smaller proportions.

It’s nice to know what people think, but I have a few concerns about the usefulness of this study. One of the main problems is that it doesn’t seem safe to assume that respondents interpret “big impact” as meaning “an impact that is independently important in determining your overall level of quality of life”. So, even if we accept that people judging something to be important makes it important (which I’m not sure it does), then we still can’t be sure whether what they are identifying is within the scope of what we’re trying to measure. For starters, I can see no justification for including a ‘medication side effects’ domain. There’s also some concern about selection and attrition. I’d guess that people with more complicated or less common health concerns would be more likely to start and finish a survey about more complicated or less common health concerns.

The main thing I took from this study is that half of respondents with chronic diseases thought that the EQ-5D-5L captured every single aspect of health that had a “big impact”, and that there wasn’t broad support for any other specific dimension.

Reducing drug wastage in pharmaceuticals dosed by weight or body surface areas by optimising vial sizes. Applied Health Economics and Health Policy [PubMed] Published 5th December 2018

It’s common for pharmaceuticals to be wasted. Not just those out-of-date painkillers you threw in the bin, but also the expensive stuff being used in hospitals. One of the main reasons that waste occurs is that vials are made to specific sizes and, often, dosage varies from patient to patient – according to weight, for example – and doesn’t match the vial size. Suppose that vials are available as 50mg and 80mg and that an individual requires a 60mg dose. One way to address this might be to allow for vial sharing, whereby the leftovers are given to the next patient. But that isn’t always possible. So, we might like to consider what the best combination of available vial sizes should be, given the characteristics of the population.

In this paper, the authors set out the problem mathematically. Essentially, the optimisation problem is to minimise cost across the population subject to the vial sizes. An example is presented for two drugs (pembrolizumab and cabazitaxel), simulating patients based on samples drawn from the Health Survey for England. Simplifications are applied to the examples, such as setting a constraint of 8 vials per patient and assuming that prices are linear (i.e. fixed per milligram).

Pembrolizumab is currently available in 50mg and 100mg vials, and the authors estimate current wastage to be 13.2%. The simulations show that switching the 50mg to a 70mg would cut wastage to 8.6%. Cabazitaxel is available in 60mg vials, resulting in 19.4% wastage. Introducing a 12.5mg vial would cut wastage by around two thirds. An important general finding, which should be self-evident, is that vial sizes should not be divisible by each other, as this limits the number of possible combinations.

Depending on when vial sizes are determined (e.g. pre- or post-authorisation), pharmaceutical companies might use it to increase profit margins, or health systems might use it to save costs. Regardless, wastage isn’t useful. Evidence-based manufacture is an example of one of those best ideas; the sort that is simple and seems obvious once it’s spelt out. It’s a rare opportunity to benefit patients, health care providers, and manufacturers, with no significant burden on policymakers.

Death or debt? National estimates of financial toxicity in persons with newly-diagnosed cancer. The American Journal of Medicine [PubMed] Published October 2018

If you’re British, what’s the scariest thing about an ‘Americanised’ (/Americanized) health care system? Expensive inhalers? A shortened life expectancy? My guess is that the prospect of having to add financial ruin to terminal illness looms pretty large. You should make sure your fear is evidence-based. Here’s a paper to shake in the face of anyone who doesn’t support universal health care.

The authors use data from the Health and Retirement Study from 1998-2014, which includes people over 50 years of age and includes new (self-reported) diagnoses of cancer. This was the basis for inclusion in the study, with over 9.5 million new diagnoses of cancer. Up to two years pre-diagnosis was taken as a baseline. The data set also includes information on participants’ assets and debts, allowing the authors to use change in net worth as the primary outcome. Generalised linear models were used to assess various indicators of financial toxicity, including change or incurrence of consumer debt, mortgage debt, and home equity debt at two- and four-year follow-up. In addition to cancer diagnosis, various chronic comorbidities and socio-demographic variables were included in the models.

Shockingly, after two years following diagnosis, 42.4% of people had depleted their entire life’s assets. Average net worth had dropped $92,000. After four years, 38.2% were still insolvent. Women, older people, people who weren’t White, people with Medicaid, and those with worsening cancer status were among those more likely to have completely depleted their assets within two years. Having private insurance and being married had protective effects, as we might expect. There were some interesting findings associated with the 2008 financial crisis, which also seemed to be protective. And a protective effect associated with psychiatric comorbidity deserves more thought.

It’s difficult to explain away any (let alone all) of the magnitude of these findings. The analysis seems robust. But, given all other evidence available about out-of-pocket costs for cancer patients in the US, it should be shocking but not unexpected. The authors describe financial toxicity as ‘unintended’. There’s nothing unintended about this. Policymakers in the US keep deciding that they’d prefer to destroy the lives of sick people than allow for the spreading of that financial risk.

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Chris Sampson’s journal round-up for 27th August 2018

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

Ethically acceptable compensation for living donations of organs, tissues, and cells: an unexploited potential? Applied Health Economics and Health Policy [PubMed] Published 25th August 2018

Around the world, there are shortages of organs for transplantation. In economics, the debate around the need to increase organ donation can be frustratingly ignorant of ethical and distributional concerns. So it’s refreshing to see this article attempting to square concerns about efficiency and equity. The authors do so by using a ‘spheres of justice’ framework. This is the idea that different social goods should be distributed according to different principles. So, while we might be happy for brocolli and iPhones to be distributed on the basis of free exchange, we might want health to be distributed on the basis of need. The argument can be extended to state that – for a just situation to prevail – certain exchanges between these spheres of justice (e.g. health for iPhones) should never take place. This idea might explain why – as the authors demonstrate with a review of European countries – policy tends not to allow monetary compensation for organ donation.

The paper cleverly sets out to taxonomise monetary and non-monetary reimbursement and compensation with reference to individuals’ incentives and the spheres of justice principles. From this, the authors reach two key conclusions. Firstly, that (monetary) reimbursement of donors’ expenses (e.g. travel costs or lost earnings) is ethically sound as this does not constitute an incentive to donate but rather removes existing disincentives. Secondly, that non-monetary compensation could be deemed ethical.

Three possible forms of non-monetary compensation are discussed: i) prioritisation, ii) free access, and iii) non-health care-related benefits. The first could involve being given priority for receiving organs, or it could extend to the jumping of other health care waiting lists. I think this is more problematic than the authors let on because it asserts that health care should – at least in part – be distributed according to desert rather than need. The second option – free access – could mean access to health care that people would otherwise have to pay for. The third option could involve access to other social goods such as education or housing.

This is an interesting article and an enjoyable read, but I don’t think it provides a complete solution. Maybe I’m just too much of a Marxist, but I think that this – as all other proposals – fails to distribute from each according to ability. That is, we’d still expect non-monetary compensation to incentivise poorer (and on average less healthy) people to donate organs, thus exacerbating health inequality. This is because i) poorer people are more likely to need the non-monetary benefits and ii) we live in a capitalist society in which there is almost nothing that money can’t by and which is strictly non-monetary. Show me a proposal that increases donation rates from those who can most afford to donate them (i.e. the rich and healthy).

Selecting bolt-on dimensions for the EQ-5D: examining their contribution to health-related quality of life. Value in Health Published 18th August 2018

Measures such as the EQ-5D are used to describe health-related quality of life as completely and generically as possible. But there is a trade-off between completeness and the length of the questionnaire. Necessarily, there are parts of the evaluative space that measures will not capture because they are a simplification. If the bit they’re missing is important to your patient group, that’s a problem. You might fancy a bolt-on. But how do we decide which areas of the evaluative space should be more completely included in the measure? Which bolt-ons should be used? This paper seeks to provide means of answering these questions.

The article builds on an earlier piece of work that was included in an earlier journal round-up. In the previous paper, the authors used factor analysis to identify candidate bolt-ons. The goal of this paper is to outline an approach for specifying which of these candidates ought to be used. Using data from the Multi-Instrument Comparison study, the authors fit linear regressions to see how well 37 candidate bolt-on items explain differences in health-related quality of life. The 37 items correspond to six different domains: energy/vitality, satisfaction, relationships, hearing, vision, and speech. In a second test, the authors explored whether the bolt-on candidates could explain differences in health-related quality of life associated with six chronic conditions. Health-related quality of life is defined according to a visual analogue scale, which notably does not correspond to that used in the EQ-5D but rather uses a broader measure of physical, mental, and social health.

The results suggest that items related to energy/vitality, relationships, and satisfaction explained a significant part of health-related quality of life on top of the existing EQ-5D dimensions. The implication is that these could be good candidates for bolt-ons. The analysis of the different conditions was less clear.

For me, there’s a fundamental problem with this study. It moves the goals posts. Bolt-ons are about improving the extent to which a measure can more accurately represent the evaluative space that it is designed to characterise. In this study, the authors use a broader definition of health-related quality of life that – as far as I can tell – the EQ-5D is not designed to capture. We’re not dealing with bolt-ons, we’re dealing with extensions to facilitate expansions to the evaluative space. Nevertheless, the method could prove useful if combined with a more thorough consideration of the evaluative space.

Sources of health financing and health outcomes: a panel data analysis. Health Economics [PubMed] [RePEc] Published 15th August 2018

There is a growing body of research looking at the impact that health (care) spending has on health outcomes. Usually, these studies don’t explicitly look at who is doing the spending. In this study, the author distinguishes between public and private spending and attempts to identify which type of spending (if either) results in greater health improvements.

The author uses data from the World Bank’s World Development Indicators for 1995-2014. Life expectancy at birth is adopted as the primary health outcome and the key expenditure variables are health expenditure as a share of GDP and private health expenditure as a share of total health expenditure. Controlling for a variety of other variables, including some determinants of health such as income and access to an improved water source, a triple difference analysis is described. The triple difference estimator corresponds to the difference in health outcomes arising from i) differences in the private expenditure level, given ii) differences in total expenditure, over iii) time.

The key finding from the study is that, on average, private expenditure is more effective in increasing life expectancy at birth than public expenditure. The author also looks at government effectiveness, which proves crucial. The finding in favour of private expenditure entirely disappears when only countries with effective government are considered. There is some evidence that public expenditure is more effective in these countries, and this is something that future research should investigate further. For countries with ineffective governments, the implication is that policy should be directed towards increasing overall health care expenditure by increasing private expenditure.

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Alastair Canaway’s journal round-up for 30th July 2018

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

Is there an association between early weight status and utility-based health-related quality of life in young children? Quality of Life Research [PubMed] Published 10th July 2018

Childhood obesity is an issue which has risen to prominence in recent years. Concurrently, there has been an increased interest in measuring utility values in children for use in economic evaluation. In the obesity context, there are relatively few studies that have examined whether childhood weight status is associated with preference-based utility and, following, whether such measures are useful for the economic evaluation of childhood obesity interventions. This study sought to tackle this issue using the proxy version of the Health Utilities Index Mark 3 (HUI-3) and weight status data in 368 children aged five years. Associations between weight status and HUI-3 score were assessed using various regression techniques. No statistically significant differences were found between weight status and preference-based health-related quality of life (HRQL). This adds to several recent studies with similar findings which imply that young children may not experience any decrements in HRQL associated with weight status, or that the measures we have cannot capture these decrements. When considering trial-based economic evaluation of childhood obesity interventions, this highlights that we should not be solely relying on preference-based instruments.

Time is money: investigating the value of leisure time and unpaid work. Value in Health Published 14th July 2018

For those of us who work on trials, we almost always attempt to do some sort of ‘societal’ perspective incorporating benefits beyond health. When it comes to valuing leisure time and unpaid work there is a dearth of literature and numerous methodological challenges which has led to a bit of a scatter-gun approach to measuring and valuing (usually by ignoring) this time. The authors in the paper sought to value unpaid work (e.g. household chores and voluntary work) and leisure time (“non-productive” time to be spent on one’s likings, nb. this includes lunch breaks). They did this using online questionnaires which included contingent valuation exercises (WTP and WTA) in a sample of representative adults in the Netherlands. Regression techniques following best practice were used (two-part models with transformed data). Using WTA they found an additional hour of unpaid work and leisure time was valued at €16 Euros, whilst the WTP value was €9.50. These values fall into similar ranges to those used in other studies. There are many issues with stated preference studies, which the authors thoroughly acknowledge and address. These costs, so often omitted in economic evaluation, have the potential to be substantial and there remains a need to accurately value this time. Capturing and valuing these time costs remains an important issue, specifically, for those researchers working in countries where national guidelines for economic evaluation prefer a societal perspective.

The impact of depression on health-related quality of life and wellbeing: identifying important dimensions and assessing their inclusion in multi-attribute utility instruments. Quality of Life Research [PubMed] Published 13th July 2018

At the start of every trial, we ask “so what measures should we include?” In the UK, the EQ-5D is the default option, though this decision is not often straightforward. Mental health disorders have a huge burden of impact in terms of both costs (economic and healthcare) and health-related quality of life. How we currently measure the impact of such disorders in economic evaluation often receives scrutiny and there has been recent interest in broadening the evaluative space beyond health to include wellbeing, both subjective wellbeing (SWB) and capability wellbeing (CWB). This study sought to identify which dimensions of HRQL, SWB and CWB were most affected by depression (the most common mental health disorder) and to examine the sensitivity of existing multi-attribute utility instruments (MAUIs) to these dimensions. The study used data from the “Multi-Instrument Comparison” study – this includes lots of measures, including depression measures (Depression Anxiety Stress Scale, Kessler Psychological Distress Scale); SWB measures (Personal Wellbeing Index, Satisfaction with Life Scale, Integrated Household Survey); CWB (ICECAP-A); and multi-attribute utility instruments (15D, AQoL-4D, AQoL-8D, EQ-5D-5L, HUI-3, QWB-SA, and SF-6D). To identify dimensions that were important, the authors used the ‘Glass’s Delta effect size’ (the difference between the mean scores of healthy and self-reported groups divided by the standard deviation of the healthy group). To investigate the extent to which current MAUIs capture these dimensions, each MAUI was regressed on each dimension of HRQL, CWB and SWB. There were lots of interesting findings. Unsurprisingly, the most important dimensions were in the psychosocial dimensions of HRQL (e.g. the ‘coping’, ‘happiness’, and ‘self-worth’ dimensions of the AQoL-8D). Interestingly, the ICECAP-A proved to be the best measure for distinguishing between healthy individuals and those with depression. The SWB measures, on the other hand, were less impacted by depression. Of the MAUIs, the AQoL-8D was the most sensitive, whilst our beloved EQ-5D-5L and SF-6D were the least sensitive at distinguishing dimensions. There is a huge amount to unpack within this study, but it does raise interesting questions regarding measurement issues and the impact of broadening the evaluative space for decision makers. Finally, it’s worth noting that a new MAUI (ReQoL) for mental health has been recently developed – although further testing is needed, this is something to consider in future.

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